Open AccessBridging the Gap Between Theory and Empirical Research in Evaluative Judgment
Author(s) -
Hassan Khosravi,
George Gyamfi,
Barbara E. Hanna,
Jason M. Lodge,
Solmaz Abdi
Publication year - 2021
Publication title -
journal of learning analytics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.084
H-Index - 7
ISSN - 1929-7750
DOI - 10.18608/jla.2021.7206
Subject(s) - bridging (networking) , learning analytics , empirical research , educational research , value (mathematics) , quality (philosophy) , psychology , conceptual framework , scale (ratio) , computer science , knowledge management , data science , epistemology , pedagogy , sociology , social science , computer network , philosophy , physics , quantum mechanics , machine learning
The value of students developing the capacity to accurately judge the quality of their work and that of others has been widely studied and recognized in higher education literature. To date, much of the research and commentary on evaluative judgment has been theoretical and speculative in nature, focusing on perceived benefits and proposing strategies seen to hold the potential to foster evaluative judgment. The efficacy of the strategies remains largely untested. The rise of educational tools and technologies that generate data on learning activities at an unprecedented scale, alongside insights from the learning sciences and learning analytics communities, provides new opportunities for fostering and supporting empirical research on evaluative judgment. Accordingly, this paper offers a conceptual framework and an instantiation of that framework in the form of an educational tool called RiPPLE for data-driven approaches to investigating the enhancement of evaluative judgment. Two case studies, demonstrating how RiPPLE can foster and support empirical research on evaluative judgment, are presented.